System for diagnosing facility apparatus, managing apparatus and diagnostic apparatus

ABSTRACT

The present invention relates to a system for managing and diagnosing a state of a facility apparatus, and an object thereof is to provide a system for diagnosing the facility apparatus wherein, if information falling under a level of abnormality is extracted from gathered information on an operating state of the facility apparatus, an advanced analysis and diagnosis section on a facility diagnosis center side performs an advanced analysis and diagnosis process and promptly notifies a user side of the information on the best way of dealing with the facility apparatus determined to be abnormal, and further uploads a facility management data analysis program from the advanced analysis and diagnosis section to a facility monitoring section on the user side so that raw information of a large information amount can be analyzed on the user side without sending it to the facility diagnosis center side.  
     A facility management data processing section ( 3   a ) signal-processes facility state detecting information detected by facility state detectors ( 2   a   , 2   b ) mounted on a facility apparatus ( 1 ), a facility state determining section ( 4 ) determines a level of the signal-processed information comparing with a management reference value and outputs it, the facility monitoring section ( 5 ) gathers and processes the information related to the level-determined facility apparatus ( 1 ) and sends it to the advanced analysis and diagnosis section ( 6 ) via a communication network ( 10 ), and the advanced analysis and diagnosis section ( 6 ) performs an advanced analysis of the information and identifies a cause of the abnormality of the facility apparatus ( 1 ) concerned and improvement measures thereof to send the identified results to the facility monitoring section ( 5 ). In addition, it is characterized in that the facility management data analysis program is uploaded from the advanced analysis and diagnosis section ( 6 ) to the facility monitoring section ( 5 ) so that the advanced analysis can be performed on the user side B.

TECHNICAL FIELD

The present invention relates to a system for managing and diagnosing astate of a facility apparatus.

BACKGROUND ART

In the past, as for management of a facility apparatus of a plant and soon of a common enterprise, it was general that, while constantlywatching operating situation of the facility apparatus, a person incharge of managing the facility apparatus further monitored a state ofthe facility apparatus at the site when an abnormality occurs as tovibration, sound, pressure, temperature and so on thereof, and stoppedits operation, as the case may be, to investigate the cause and urgentlyrepair it or replace a part, or to refer it to a facility apparatusmanufacturer and consider countermeasures comparing with it when thesituation further became serious.

In the aforementioned example in the past, however, a judgment was madebased on personal knowledge and experience to the extent that the personin charge of managing the facility apparatus can deal with it, so thatthe judgment result was not necessarily correct and there were thecases, according to circumstances, where a wrong judgment was made andthe judgment result lacked objectivity.

On the other hand, it has been increasingly demanded in recent years toreduce total costs of the plant, for the sake of safe operation andimprovement in productivity thereof, by means of improved accuracy offacility management, increased efficiency of technically trainedpersonnel for the facility management, and improved reliability of thefacility apparatus. In addition, it is becoming a common understandingthat predictive diagnosises and steady maintenance planning should bethoroughly performed for various facility apparatuses, particularly forkey apparatuses.

For instance, as for the plant in which a large number of rotatingapparatuses and so on are placed, the person in charge of managing thefacility apparatus periodically performs maintenance work whileperforming daily operating work. However, it requires expertise in itsown way to solve problems related to predictive maintenance such asfacility diagnosis, predictive diagnosis and optimum operatingconditions of the rotating apparatuses or a grasp of remaining lifethereof, and so there is a limit to what can be done only by the personin charge of managing the facility apparatus.

Therefore, it is desirable to have the technically trained personnelwith such expertise stationed in the plant, and yet it is difficult inmany cases in consideration of the cost aspect of the plant operationsuch as the increased efficiency of the personnel.

The present invention solves the above described problem, and an objectthereof is to provide a system for diagnosing the facility apparatus,wherein minimum operating situation of the facility apparatus is graspedand controlled by constantly measuring it with a device or manually togather various kinds of data, and if information falling under a levelof abnormality is extracted from the gathered information, theinformation is promptly sent to a facility diagnosis center which is aspecialized technological group, where an advanced analysis anddiagnosis section performs an advanced analysis and diagnosis process tothe information and promptly notifies the facility apparatus managementside of the information on the best way of dealing with the facilityapparatus determined to be abnormal, and uploads a facility managementdata analysis program from the advanced analysis and diagnosis sectionto a facility monitoring section on the user side in the case where itis necessary to further analyze various kinds of detailed on-site data,so that raw information of a large information amount can be analyzed onthe user side without sending it to the facility diagnosis center side.

DISCLOSURE OF THE INVENTION

A representative configuration of a system for diagnosing a facilityapparatus related to the present invention has facility state detectingmeans mounted on the facility apparatus for detecting a state of thefacility apparatus, a facility management data processing section forsignal-processing and outputting facility state detecting informationdetected by the above described facility state detecting means, afacility state determining section for determining a level of theinformation outputted from the above described facility management dataprocessing section comparing with a management reference value andoutputting it, a facility monitoring section for gathering, processingand outputting information related to the facility apparatuslevel-determined and outputted from the above described facility statedetermining section, and an advanced analysis and diagnosis section forperforming an advanced analysis of the information outputted from theabove described facility monitoring section and identifying a cause ofan abnormality of the facility apparatus and improvement measuresthereof to send the identified results to the above described facilitymonitoring section.

Furthermore, it has the configuration wherein the above describedfacility monitoring section and the above described advanced analysisand diagnosis section are capable of mutual communication via acommunication network, and a facility management data analysis programis uploaded from the above described advanced analysis and diagnosissection to the above described facility monitoring section.

As the present invention is constituted as described above, facilitystate detecting information detected by the facility state detectingmeans is signal-processed by the facility management data processingsection on the user side managing the facility apparatus, andthereafter, the level is determined comparing with the managementreference value by the facility state determining section, and theinformation related to the level-determined facility apparatus from thefacility monitoring section is gathered and processed so as to beoutputted to a facility diagnosis center which is a specializedtechnological group via a communication network.

On the facility diagnosis center side, the advanced analysis anddiagnosis section having received the information outputted from thefacility monitoring section on the user side performs the advancedanalysis of the information to identify a cause of an abnormality of thefacility apparatus and improvement measures thereof so as to send theidentified results to the facility monitoring section on the user sidevia the communication network. Thus, it is possible, on the user sidemanaging the facility apparatus, to promptly acquire the information onthe best way of dealing with the facility apparatus determined to beabnormal so as to handle it.

In this case, if the advanced analysis and diagnosis section determinesthat accuracy of the diagnosis can be rendered higher by furtherperforming another advanced analysis, the facility management dataanalysis program is further uploaded as a secondary process from theadvanced analysis and diagnosis section on the facility diagnosis centerside to the facility monitoring section on the user side via thecommunication network so that the advanced analysis is performed againon the user side.

As the facility management data analysis program is uploaded to the userside and the advanced analysis is performed again on the user side, onlya small information amount solely on analysis results is sent to thefacility diagnosis center side without necessity to send raw data of anenormous information amount such as the facility state detectinginformation detected by the facility state detecting means to thefacility diagnosis center side, and so a burden of information transferon the communication network is alleviated.

In addition, security of the information is improved because the rawdata is not exchanged on the communication network.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram showing a configuration of a system fordiagnosing a facility apparatus related to the present invention.

FIG. 2 is a block diagram showing a user-side configuration of thesystem for diagnosing the facility apparatus related to the presentinvention.

FIG. 3 is a diagram showing a configuration example of a communicationnetwork between a facility monitoring section and an advanced analysisand diagnosis section.

FIG. 4 is a block diagram showing the configurations of facility statedetecting means and the advanced analysis and diagnosis section.

FIG. 5 is a block diagram showing the configuration of the advancedanalysis and diagnosis section.

FIG. 6 is a diagram showing a detailed configuration of an advanced dataanalysis section.

FIG. 7 is a diagram for explaining a relationship between a signalprocessing recipe and a facility management data analysis program group.

FIG. 8 is a diagram showing an example of a display screen image of thefacility monitoring section.

FIG. 9 is a diagram showing an example of the display screen image ofthe facility monitoring section.

FIG. 10 is a diagram showing an example of a diagnostic result list sentfrom the advanced analysis and diagnosis section.

FIG. 11 is a diagram showing an example of primary diagnostic resultssent from the advanced analysis and diagnosis section.

FIG. 12 is a diagram showing an example of secondary diagnostic resultssent from the advanced analysis and diagnosis section.

FIG. 13 is a diagram showing a relationship between the cause andresults diagnosed by the advanced analysis and diagnosis section.

FIG. 14 is a diagram showing an example of output undergone a secondaryprocess by using the facility management data analysis program uploadedon the user side.

FIG. 15 is a diagram showing an example of a rolling bearing abnormalvibration determination criterion.

BEST MODE FOR CARRYING OUT THE INVENTION

Next, an embodiment of a system for diagnosing a facility apparatusrelated to the present invention will be concretely described by usingthe drawings. FIG. 1 is a block diagram showing a configuration of thesystem for diagnosing the facility apparatus related to the presentinvention, FIG. 2 is a block diagram showing a user-side configurationof the system for diagnosing the facility apparatus related to thepresent invention, FIG. 3 is a diagram showing a configuration exampleof a communication network between a facility monitoring section and anadvanced analysis and diagnosis section, FIG. 4 is a block diagramshowing the configurations of facility state detecting means and theadvanced analysis and diagnosis section, FIG. 5 is a block diagramshowing the configuration of the advanced analysis and diagnosissection, FIG. 6 is a diagram showing a detailed configuration of anadvanced data analysis section, and FIG. 7 is a diagram for explaining arelationship between a signal processing recipe and a facilitymanagement data analysis program group.

In addition, FIGS. 8 and 9 are diagrams showing examples of displayscreen images of the facility monitoring section, FIG. 10 is a diagramshowing an example of a diagnostic result list sent from the advancedanalysis and diagnosis section, FIG. 11 is a diagram showing an exampleof primary diagnostic results sent from the advanced analysis anddiagnosis section, FIG. 12 is a diagram showing an example of secondarydiagnostic results sent from the advanced analysis and diagnosissection, FIG. 13 is a diagram showing a relationship between the causeand results diagnosed by the advanced analysis and diagnosis section,FIG. 14 is a diagram showing an example of output having undergone asecondary process by using the facility management data analysis programuploaded on the user side, and FIG. 15 is a diagram showing an exampleof a rolling bearing abnormal vibration determination criterion.

In FIGS. 1 to 7, reference symbol A denotes a plant or the like on auser side B in which a large number of facility apparatuses such asrotating apparatuses are placed, and C denotes a facility diagnosiscenter side having a specialized technological group knowledgeable aboutdiagnostic operation of the facility apparatuses, located at a distantplace from the user side B.

The plant A has a large number of facility apparatuses 1 for deliveringvarious functions such as rotating apparatuses including a fan 1 a and apump 1 b, where various facility apparatuses 1 have facility statedetectors 2 a and 2 b comprised of various sensor elements and so onwhich are facility state detecting means for detecting the state of thefacility apparatuses 1 mounted thereon.

The facility state detectors 2 a and 2 b send daily facility statedetecting information on the facility apparatuses 1 to a facilitymanagement data processing section 3 a of a monitoring apparatus 3, andthe facility state information signal-processed by the facilitymanagement data processing section 3 a is sent to a facility statedetermining section 3 b.

The facility state determining section 3 b determines a level of theinformation outputted from the facility management data processingsection 3 a comparing with a preset management reference value andoutputs it. The facility management data processing section 3 a and thefacility state determining section 3 b are placed at the site around thefacility apparatuses 1 in the plant A.

For instance, vibration raw waveform data is collected by the facilitystate detectors 2 a and 2 b such as vibration sensors provided to thefacility apparatuses 1, and the vibration raw waveform data undergoessignal processes such as a filter process, an integration process, anaveraging process and a peak detection process in the facilitymanagement data processing section 3 a, so that the facility statedetermining section 3 b compares to preset thresholds the values offacility state parameters such as an O/A value (output of the averagingprocess) and a peak value representing the state of the facilityapparatuses 1 obtained as a result of the signal processes so as to makea primary determination of the state of the facility apparatuses 1.

The information determined by the facility state determining section 3 bis sent to a facility monitoring section 5 for centrally managing thefacility apparatuses 1 of the entire plant A, and the facilitymonitoring section 5 gathers, processes, outputs and stores theinformation related to the facility apparatuses 1 level-determined andoutputted from the facility state determining section 3 b. To be morespecific, the facility monitoring section 5 stores the facility stateparameters as trend management data, and also gathers and managesfacility-related information such as specifications and history of thefacility apparatuses 1.

The facility monitoring section 5 on the user side B and an advancedanalysis and diagnosis section 6 on a facility diagnosis center side Care constituted to be capable of mutual communication via acommunication network 10 such as a network, the Internet or a publiccircuit, and the facility monitoring section 5 gathers and processes theinformation on the facility apparatus 1 determined to be abnormal by thefacility state determining section 3 b and sends it to the facilitydiagnosis center side C via the communication network 10.

To be more specific, in the case of being determined to be abnormal bythe facility state determining section 3 b, it sends the values of thefacility state parameters which are primary process results as well asthe facility-related information such as the trend management datagathered and managed by the facility monitoring section 5,specifications and history of the facility apparatus 1 to the facilitydiagnosis center side C via the communication network 10.

The information sent from the facility monitoring section 5 on the userside B is received by the advanced analysis and diagnosis section 6 onthe facility diagnosis center side C, and the advanced analysis anddiagnosis section 6 identifies a cause of an abnormality of the facilityapparatus and improvement measures thereof by automatically analyzingthe information outputted from the facility monitoring section 5 to sendthe identified results to the facility monitoring section 5.

As shown in FIG. 4, the advanced analysis and diagnosis section 6 has anautomatic diagnosis section 6 a provided thereto for evaluatingdiagnostic information sent from the user side B and automaticallydiagnosing an abnormal part, the cause of an abnormality, remaininglife, countermeasures (improvement method) and so on.

In addition, as shown in FIGS. 5 and 6, the advanced analysis anddiagnosis section 6 has an advanced data analysis section 6 b forsending to the facility monitoring section 5 on the user side B theprogram for advanced data analyses such as an analysis by atime-frequency analysis technology for arbitrarily decomposing a rawwaveform signal detected by the facility state detectors 2 a and 2 binto wavelets, and furthermore, an SDP (Symmetrized Dot Patterns)analysis by a visibility analysis technology of plottng the raw waveformsignal detected by the facility state detectors 2 a and 2 b on a subjectcoordinate, and furthermore, a dimensionless feature parameter which isa signal processing technology for characterizing a characteristic of asignal and so on by rendering a dimensional characteristic amount suchas vibration and sound dimensionless and thereby detecting theabnormality, and furthermore, a multi-variate analysis which is ananalysis technology for pursuing the cause by using a plurality ofmutually correlated signals so as to have a detailed analysis performed,improve accuracy of abnormality detection and send the analysis resultsto the automatic diagnosis section 6 a.

In addition, the advanced data analysis section 6 b has theaforementioned signal processing recipes of an SDP file 11 a, a waveletfile 11 b, an FFT file 11 c, a dimensionless feature parameter file 11d, a multi-variate analysis file 11 e and another analysis file 11 fprovided thereto, and performs diagnosis at the advanced analysis anddiagnosis section 6 based on the information outputted from the facilitymonitoring section 5, and in the case where it is necessary to performadditional diagnosis, it extracts a predetermined facility managementdata analysis program from a facility management data analysis programgroup 12 shown in FIGS. 6 and 7 so as to render it as an electronic filein the SDP file 11 a, wavelet file 11 b, FFT file 11 c, dimensionlessfeature parameter file 11 d, multi-variate analysis file 11 e andanother analysis file 11 f of each signal processing recipe and uploadthem from the advanced analysis and diagnosis section 6 on the facilitydiagnosis center side C to the facility monitoring section 5 on the userside B.

In addition, as shown in FIGS. 4 and 5, the advanced analysis anddiagnosis section 6 analyzes a changing trend from data on change overtime sent from the facility state determining section 3 b on the userside B and sends the analysis results to the automatic diagnosis section6 a. Moreover, the advanced analysis and diagnosis section 6 has a trendmanagement section 6 c for having the output sent to the automaticdiagnosis section 6 a transferred to a life prediction section topredict life and a life prediction section 6 d for predicting life basedon the data on change over time managed by the trend management section6 c, calculating life prediction by a unique formula acquired from pastdiagnostic performances and sending the analysis results to theautomatic diagnosis section 6 a provided thereto.

In addition, the advanced analysis and diagnosis section 6 has athorough diagnosis section 6 e for detecting a characteristic frequencyfrom thorough diagnosis Information by Fast Fourier transform (FFT)which is a representative frequency analysis technique, comparing it tothe thorough diagnosis information of normal time and sending theanalysis results to the automatic diagnosis section 6 a providedthereto.

In addition, the advanced analysis and diagnosis section 6 has animprovement method selecting section 6 f for selecting a most suitableimprovement method according to the specifications and diagnosticcontents of the facility apparatus 1 from an improvement method databaseconstructed based on the diagnoses and improvements implemented in thepast and using the results thereof as diagnostic results of theautomatic diagnosis section 6 a, and a maintenance information section 6g for managing the specifications, maintenance planning, maintenanceperformances and so on, performing an automatic analysis based on thisinformation and contributing to concrete countermeasures, improvementmethods and so on.

The facility monitoring section 5 on the user side B and the advancedanalysis and diagnosis section 6 on the facility diagnosis center side Care connected by the communication network 10 such as a network, theInternet or a public circuit, and various kinds of information such asthe facility state detecting information and a diagnostic reportmutually exchanged between them is rendered as the electronic file andis sent and received by e-mail and so on.

Reference numeral 9 in FIG. 3 denotes a firewall installed between anexternal network and an internal network, which is intended to blockunauthorized break-in by a malicious third party from the outside andleak, falsification and destruction of the data and so on thereby.Moreover, it may be a configuration without the firewall 9 in the casewhere security is ensured.

Moreover, a leased line, a communication satellite or the like may beutilized as another communication network 10 for connecting the facilitymonitoring section 5 on the user side B to the advanced analysis anddiagnosis section 6 on the facility diagnosis center side C.

The information sent from the facility monitoring section 5 on the userside B undergoes an advanced analysis in the advanced analysis anddiagnosis section 6, and the results thereof are sent back to thefacility monitoring section 5 on the user side B, and based on thatinformation, the facility monitoring section 5 notifies the facilityapparatus 1 determined to be abnormal of the best action so as to dealwith it at once.

As for the facility state detecting means mounted on a large number offacility apparatuses 1, an online apparatus and a portable facilitydiagnostic measuring apparatus are adopted as standard diagnosis andthorough diagnosis in terms of rotating machine vibration diagnosis, andan oil diagnosing apparatus is adopted in terms of oil diagnosis asshown in FIG. 4 for instance.

Here, the standard diagnosis determines whether the facility is normalor abnormal from a vibration level and the change over time thereof andalso briefly determines the cause, part, degree, life prediction and soon thereof, whereas the thorough diagnosis analyzes in detail an eventundeterminable and so on.

In addition, the facility state detecting means in piping managementperforms a nondestructive inspection by utilizing a UT (Ultra Sonic) orcorrosion diagnosis with an infrared camera for instance, and thefacility state detecting means in tank bottom plate diagnosis performsthe nondestructive inspection of the entire tank bottom plate byutilizing the UT for instance, and the facility state detecting means ina general static apparatus performs the nondestructive inspection byutilizing the UT or the corrosion diagnosis with the infrared camera.

In addition, a daily inspection system shown at the upper right of FIG.4 implements the information on plant inspection performed daily by anoperator by inputting it to a portable terminal on site inspection so asto realize data management on a personal computer, mainly handlingprocess information (temperature and pressure during operation), leakrelated to the facility and sensory information such abnormal noise.

In addition, although the facility state detectors 2 a and 2 b comprisedof the sensor elements and so on mounted on the facility apparatuses 1constantly detect various status conditions such as vibration,temperature, pressure, lubricant components, sound, currents andvoltage, they may also be portable facility diagnostic measuringapparatuses with which an operating worker measures various kinds ofinformation when making a tour of the facility apparatuses 1 instead ofmounting the facility state detectors 2 a and 2 b directly on thefacility apparatuses 1.

For instance, if an example of the case where the facility apparatuses 1are the rotating apparatuses is described in detail, the facility statedetecting information on the rotating apparatuses is sent to thefacility management data processing section 3 a from the facility statedetectors 2 a and 2 b mounted on the large number of rotatingapparatuses.

The facility management data processing section 3 a performs signalprocesses such as the filter process and speed conversion to the signalreceived as the primary process, and further performs a peak process, afrequency analysis and so on to output (primary process output) adetermination signal comprised of an acceleration overall value, anacceleration peak value, a speed overall value and soon necessary todiagnose vibration situation of the rotating apparatuses concerned andsends it to the facility state determining section 3 b.

The facility state determining section 3 b has a management referencevalue created in advance on the facility diagnosis center side Cinputted thereto, and compares to the above described managementreference value the determination signal which is the informationoutputted from the facility management data processing section 3 a so asto determine the level of the rotating apparatuses concerned. Normally,the determined levels are broadly classified into “normal” and“abnormal,” and “abnormal” is further divided into “caution” and“danger.” The determined determination signal is recorded in thefacility monitoring section 5.

In the case where it is determined as “caution” or “danger” indicatingbeing “abnormal” by the facility state determining section 3 b, thefacility monitoring section 5 records predetermined information such asmeasurement data and history data of the rotating apparatuses concernedand the measurement data of another rotating apparatus of the same modeloperating at a different location as well as the determination signal(primary process output result) sent from the facility state determiningsection 3 b, and automatically transmits such information by e-mail tothe advanced analysis and diagnosis section 6 after arranging it in theelectronic file attached to the e-mail via the communication network 10such as a network, the Internet or a public circuit. In addition, itautomatically transmits the information periodically (once a day forinstance) in the case of “normal.”

Moreover, it may also be the method of downloading the data from thefacility monitoring section 5 by using a monitoring screen in a homepage format from the facility diagnosis center side C.

To be more specific, according to this embodiment, the facilitymonitoring section 5 outputs it by attaching abnormality data in thecase of “abnormal” in addition to whether or not there is anabnormality, and sends it to the advanced analysis and diagnosis section6.

The facility state determining section 3 b has a function of checkingwhether or not the information determined as “abnormal” is a temporaryphenomenon due to disturbance, and thus, the information determined as“abnormal” for a cause other than the temporary phenomenon is sent tothe advanced analysis and diagnosis section 6.

FIGS. 8 and 9 are the examples of images displayed on the facilitymonitoring section 5 on the user side B to be sent to the advancedanalysis and diagnosis section 6, where FIG. 8 shows a measurement datalist related to the rotating apparatuses concerned, and FIG. 9 is agraph showing the change over time of a measurement point of a specificrotating apparatus of the rotating apparatuses concerned.

A determination field 7 a shown in FIG. 8 has distinction of normal “◯,”caution “Δ,” and danger “×” recorded therein. In addition, as for thegraph of the change over time shown in FIG. 9, a vertical axis shows avibration value (mm/sec) and a horizontal axis shows a date, and thegraph of the change over time shown in FIG. 9 is displayed by clickingon a graph display button 7 e after selecting a channel number 7 c and aperiod type 7 d of “1” to “32” in a selection field 7 b on the screen inFIG. 8.

Only the information on the rotating apparatuses determined as caution“Δ” and danger “×” in the determination field 7 a in FIG. 8 is sent fromthe facility monitoring section 5 to the advanced analysis and diagnosissection 6 to undergo the advanced analysis. If various kinds ofinformation on the rotating apparatuses shown in FIGS. 8 and 9 is sentfrom the facility monitoring section 5 to the advanced analysis anddiagnosis section 6, the advanced analysis and diagnosis section 6performs the advanced analysis of the information on the rotatingapparatuses determined as caution “Δ” and danger “×” indicated in thedetermination field 7 a in FIG. 8.

The advanced analysis and diagnosis section 6 performs the advancedanalysis of the information on the rotating apparatuses determined ascaution “Δ” and danger “×” which is sent, and extracts and identifiesnecessary items such as the cause, most appropriate countermeasures andfuture maintenance planning so as to send them back by e-mail to thefacility monitoring section 5 in the plant A on the user side B via thecommunication network 10 such as a network, the Internet or a publiccircuit. Moreover, it is also possible to send them by facsimile ordeliver them as a document by mail.

To be more specific, the advanced analysis is performed as to therotating apparatuses having nine measurement points of which channelnumbers in FIG. 8 are “10” and “13” to “20,” and thereafter, thediagnostic results shown in FIG. 10 are sent back to the facilitymonitoring section 5 from the advanced analysis and diagnosis section 6.

FIG. 10 is an example of the image of an extruder which is an example ofthe rotating apparatus sent from the advanced analysis and diagnosissection 6, and if a “✓” mark entered in a primary diagnosis resultsfield 8 a is selected and clicked on, the primary diagnosis results withcomments of “Cause” and “Countermeasures” in writing as exemplified inFIG. 11 are attached.

As shown in FIG. 11, the diagnosis results are expressed affirmativelyto avoid an expression which may confuse the determination on the userside B and are also expressed concretely to allow countermeasures to beimmediately taken.

In the case where, in performing the advanced analysis of theinformation on the rotating apparatuses determined as caution “Δ” anddanger “×,” the advanced analysis and diagnosis section 6 determinesthat further precise analyses thereof needs to be performed, it requeststhe facility monitoring section 5 to extract further necessaryinformation, and additionally analyzes the new information sent from thefacility monitoring section 5 so that the same diagnostic results asshown in FIG. 10 are sent back to the facility monitoring section 5 fromthe advanced analysis and diagnosis section 6.

Although it is not shown in FIG. 10, if the “✓” mark entered in asecondary diagnosis results field 8 b as with the primary diagnosisresults field 8 a is selected and clicked on, the secondary diagnosisresults with comments of “Instruction” and “Determination” in writing asexemplified in FIG. 12 are attached.

As the facility monitoring section 5 on the user side B and the advancedanalysis and diagnosis section 6 on the facility diagnosis center side Care connected by the communication network 10 such as a network, theInternet or a public circuit to allow bi-directional communication, theuser side B can seek satisfactory explanation on the diagnosis resultsof the rotating apparatuses from the facility diagnosis center side C bye-mail, telephone and so on.

Next, the configuration of the advanced analysis and diagnosis section 6will be described in detail. The advanced analysis and diagnosis section6 has recorded and accumulated therein facility apparatus specificationinformation on various apparatuses and parts constituting each ofvarious facility apparatuses 1 such as standards and dimensions,manufacturer, date of manufacture, and various specification items(number of revolutions, axis diameter, working temperature and so on,for instance), maintenance history information such as date ofinstallation, operation records and repair records, and measured valuehistory information acquired so far by inspecting and diagnosing thefacility apparatus land so on as to each of various facility apparatuses1 in many fields placed in the plant A.

Furthermore, it has various facility apparatuses 1 classified accordingto size, loaded condition, installation environment and soon thereof,and has systematically arranged, recorded and accumulated therein thedata wherein a vibration state, remaining life and so on of the facilityapparatus under optimum operating conditions are statistically andtheoretically calculated as well as the causes of the abnormalities asto abnormal phenomena which occurred in the past and the countermeasurescomparing with them and so on.

For instance, in the case where the advanced analysis and diagnosissection 6 diagnoses the vibration state of a predetermined rotatingapparatus, the advanced analysis and diagnosis section 6 has alreadyinputted therein various kinds of information such as the number ofrevolutions, axis diameter, loaded condition, lubricated condition andinstalled condition on population of the rotating apparatuses of thefiled to which the rotating apparatus belongs to, so that it can grasp apertinent vibration state of the population of the rotating apparatus.

And it is possible to determine the level of the vibration state of thepredetermined rotating apparatus by adopting these pertinent numericalvalues as the management reference values and comparing them to themeasured values of the vibration state of the predetermined rotatingapparatus.

As for the management reference values to be the criteria, for instance,the rolling bearing abnormal vibration determination criteria shown inFIG. 15 have a horizontal axis which is a DN value (axis diameter xnumber of revolutions) and a vertical axis which is a vibrationacceleration value, and if the DN value of the facility is known, therecan be found, from that position upward in the vertical axis direction,the graphs of normal, caution, danger and so on which are respectivemanagement thresholds. The criteria were created by arranging andconstructing the diagnostic performance data.

Furthermore, it is possible to grasp the cause of the abnormality(structural abnormal condition, bearing abnormal condition and so on forinstance) of the predetermined rotating apparatus by accumulating themaintenance history information and measured value history informationon the population of the rotating apparatuses, and in that case, it isfeasible to present the best countermeasures as to what action should betaken (an improvement method database 6 f 1 in FIG. 5).

Likewise, it is possible to predict how long the current state continuesand what state it thereby develops to, that is, to analogize theremaining life of the predetermined rotating apparatus (remaining lifedetermination database 6 d 1 in FIG. 5).

These can be statistically and theoretically calculated based on thefacility apparatus specification information, maintenance historyinformation and measured value history information and so on on therotating apparatuses accumulated in the advanced analysis and diagnosissection 6.

If it is generally assumed that the facility apparatuses 1 manufacturedwith the same material and the same specifications are operated underthe same conditions, the facility apparatuses 1 have the identicalhistory as a matter of course. However, it is almost impossible inreality that the facility apparatuses 1 are exactly the same, and socausal relationship of the facility apparatuses 1 determined as“abnormal” is very wide-ranging and complicated.

Therefore, it is possible to classify a large amount of data obtainedfrom the actual facility apparatuses 1 according to size, loadedcondition, installation environment and so on thereof based ondestructive physics and statistical theory and systematically arrangeand accumulate the information to compare the data showing the currentstate of the subject facility apparatus 1 to the above describedaccumulated information on the population so as to diagnose the currentfacility state of the subject facility apparatus 1 (automatic diagnosissection 6 a).

Furthermore, it is possible to analogize how long the facility apparatus1 continues the current state and what state it thereby develops to, orin the case where it develops to an abnormal state, what countermeasuresshould be taken to block it, so that effective planning maintenancemeasures can be constructed as a result (life prediction section 6 d,improvement method selecting section 6 f).

To be more specific, the advanced analysis and diagnosis section 6 hasall the information and data on various facility apparatuses 1 placed ina number of the plants A recorded and accumulated therein, and it isthus possible to construct planning maintenance of various facilityapparatuses 1, not to mention the facility diagnosis thereof, bycomposing a theoretical formula to allow calculation of a general trendon the basis of the information and data and improving precision of thetheoretical formula while comparing the results of the formula and theactual state of the facility apparatuses 1 and correcting coefficientsthereof one after another in the meantime.

Next, a concrete example of leading to the diagnostic results of thefacility apparatuses 1 in the advanced analysis and diagnosis section 6will be described by using FIG. 13. FIG. 13 shows a part of a diagnosticknowledge matrix table stored in the advanced analysis and diagnosissection 6 in order to lead to the diagnostic results of a predeterminedair blower proper. As a matter of course, the configuration of thediagnostic knowledge matrix table is classified according to the modelconstituting each facility apparatus 1 (a fan or a compressors forinstance), and so each table is different.

The horizontal axis of the diagnostic knowledge matrix table shown inFIG. 13 has the abnormal phenomena which may occur classified into alarge number of items, and the vertical axis Is comprised of many itemssuch as the time of abnormality occurrence, point of abnormalityoccurrence, abnormality mode, change of abnormality over time and partslineup of the facility apparatus 1, where the items concerned are markedwith “●.” These are not only marked in terms of statistics andexperience, but are also marked based on the above-mentioned theoreticalcalculation. And as mentioned above, if the information on thepredetermined air blower proper is sent from the facility monitoringsection 5 to the advanced analysis and diagnosis section 6, the items ofthe vertical axis in the diagnostic knowledge matrix table in FIG. 13are automatically marked.

And as a result of the marking, the diagnostic knowledge matrix table asthe population of the air blower proper already constructed in theadvanced analysis and diagnosis section 6 is compared, contrasted andcalculated with the information on the above described predetermined airblower proper so as to lead to the diagnostic results of thepredetermined air blower proper which are the same as those shown inFIG. 10.

Furthermore, knowledge in writing in which the cause of occurrence,countermeasures, maintenance planning and so on are written isconstructed to work with the diagnostic knowledge matrix table as toeach of the large number of abnormal phenomena constituting thediagnostic knowledge matrix table which may occur, and so the diagnosticresults as the same comments on the predetermined air blower proper asshown in FIGS. 11 and 12 are automatically composed and synthesized bythe knowledge in writing by comparing, contrasting and calculating theinformation on the predetermined air blower proper with the diagnosticknowledge matrix table.

However, the above configuration can only perform the signal processingprepared in advance in the facility management data processing section 3a, and so it can only use the facility state parameters which areprocessing results thereof. In addition, in the case where there is aneffective signal process (facility state parameter) as to a certainphenomenon, it is necessary to incorporate that function into thefacility management data processing section 3 a placed on the user sideB each time, so that a problem of burdensome maintenance and updatingoccurs. Moreover, it is possible to incorporate all the presumed signalprocesses into the facility management data processing section 3 a inadvance, yet it is not efficient but uneconomical to incorporate all thefunctions of low frequency of use.

Thus, according to this embodiment, it is possible to process outputsignals of the facility state detectors 2 a and 2 b in the facilitymanagement data processing section 3 a, and furthermore, in the casewhere it is necessary to lead raw waveforms of the output signals of thefacility state detectors 2 a and 2 b to the facility state determiningsection 3 b by performing various advanced processes rather thanimmediately determining them in the facility state determining section 3b, to be equipped with a facility management data analysis programnecessary for the advanced analytic processes in the advanced dataanalysis section 6 b, upload the facility management data analysisprogram to the user side B by a remote process from the facilitydiagnosis center side C, process the output signals of the facilitystate detectors 2 a and 2 b to be processed on the user side B via thecommunication network 10 such as a network, the Internet or a publiccircuit, and send back the processing results to the facility diagnosiscenter side C so as to alleviate a transmission load on thecommunication network 10 and also solve the above-mentioned problems.

To be more specific, in the case where the advanced analysis anddiagnosis section 6 determines that the advanced analysis is necessaryfrom another viewpoint, an instruction to generate a secondary processprogram is sent from the automatic diagnosis section 6 a to the advanceddata analysis section 6 b, and the necessary facility management dataanalysis program is selected and extracted as appropriate from thefacility management data analysis program group 12 so that each facilitymanagement data analysis program for the secondary process is generatedas the electronic file as shown in FIGS. 6 and 7.

FIGS. 6 and 7 show examples of the case where the FFT file 11 c iscreated from the signal processing recipe. In the case of performing theadvanced analysis by the Fast Fourier transform (FFT) which is arepresentative frequency analysis technique, the averaging process isperformed first, and then a waveform cutout process is performed by atime window, and the analytic process is performed thereafter.

The facility management data analysis program group 12 has programsgrouped according to various functions such as various averaging processprograms 12 a including a time average process (Average), RMS (Root MeanSquare) and so on, various time windows programs 12 b including hanningwindow, hamming window and so on, and various analytic process programs12 c including the Fourier transform, wavelets and so on, and furtherhas requirements for various programs to operate, output forms of theprograms and so on stored therein.

The facility management data analysis program group 12 has an object (asmall program having each function) integrating the data itself and theprocess for handling the data, and the advanced data analysis section 6b instructed by the automatic diagnosis section 6 a to generate thesecondary process program selects and combines the best suited objectsbased on the contents of a signal processing recipe 11 so as toautomatically generate the secondary process program. In addition, eachobject performs the process it has, updates and refers to the data, andfurther exchanges messages with the objects having other functions andthereby performs collaboration among the objects.

Exchange among the objects can be dispersively processed because of amechanism in which the objects themselves do not need to mutually knowwhere the other object exists. Thus, it is possible, by rendering thesignal processes as the objects and uniting the objects according to thepurposes, to implement the environment for fitly uploading necessaryanalytic processes to the user side B.

The averaging process is the process implemented for the sake of, as toa distorted waveform of which periodic vibration of a period T includesa harmonic in addition to a basic waveform and a random waveformcomprised of frequency components of a plurality of periods,representing an amplitude level of these waveforms. And the time averageprocess (Average) and RMS (square roots of distribution) are indicatedby the following formula 1 respectively. $\begin{matrix} {{{Formula}\quad 1}\quad\begin{matrix}{{Average}( {{time}\quad{average}\quad{process}} )} \\{x = {\lim\limits_{{\Delta\quad T}arrow\infty}{\frac{1}{T}{\int_{0}^{T}{{x(t)}\quad{\mathbb{d}t}}}}}} \\{{RMS}( {{Root}\quad{Mean}\quad{Square}} )} \\{x_{rims} = \sqrt{\lim\limits_{Tarrow\infty}{\frac{1}{T}{\int_{0}^{T}{{x(t)}^{2}\quad{\mathbb{d}t}}}}}}\end{matrix}} \} & (1)\end{matrix}$

In addition, as for periodicity when performing digital Fouriertransform, a joining portion of the waveforms is problematic. Forinstance, when analyzing a spectrum of a certain waveform, a highfrequency component generated from the joining portion of the periods isanalyzed together, and this high frequency is not the component existingin the original waveform so that, if the waveform of a finite section ofan analysis subject is multiplied by a function of which both ends aregently attenuated and then digital Fourier transform is performedthereto, the spectrum having eliminated the high frequency generatedfrom the joining portion can be observed. The function of which bothends are gently attenuated for waveform cutout to be utilized for such apurpose is called time windows.

There are various time windows devised, which are creatively usedaccording to differences in analysis purposes and qualities of thewaveforms respectively. As for the time windows, representative ones arethe hamming window (suited to the analysis of those having closefrequency components) and the hanning window, (suited to the analysis ofthose having not so close frequency components).

The Fourier transform is a representative frequency analysis forconverting a complicated signal into an aggregate of a large number ofsine wave groups, and the wavelet is a time-frequency analysis forarbitrarily decomposing the raw waveform signal into wavelets.

And on receiving the instruction to generate the secondary processprogram from the automatic diagnosis section 6 a, the advanced dataanalysis section 6 b selects and combines the best suited programs ofvarious kinds from the facility management data analysis program group12.

In the case where the FFT is selected as the secondary process forinstance, to generate the FFT file 11 c, the time average process(Average) is selected from an averaging process program 12 a accordingto the form of fluctuation and frequency band of the subject signal, thehamming window is selected from a time windows program 12 b, the Fouriertransform is selected from the analytic process programs 12 c, andfurthermore, related definitions, connections, requirements for variousprograms to operate, output forms of the programs and so on areconformed so as to generate the secondary process program and render itas the electronic file (11 c′).

The electronic file 11 c′ having the facility management data analysisprogram to be the secondary process program generated by the advanceddata analysis section 6 b on the facility diagnosis center side C storedtherein is uploaded to the facility monitoring section 5 on the userside B via the communication network 10 as shown in FIG. 2, andfurthermore, the facility monitoring section 5 sends the predeterminedfacility management data analysis program from the uploaded electronicfile 11 c′ to the facility management data processing section 3 a.

In the facility management data processing section 3 a, the facilitystate detecting information detected by the facility state detectors 2 aand 2 b to be the facility state detecting means is signal-processed andoutputted by the predetermined facility management data analysis programwhich was sent, the information outputted from the facility managementdata processing section 3 a is level-determined comparing with themanagement reference value and outputted by the facility statedetermining section 3 b, and the information related to the facilityapparatuses 1 level-determined and outputted by the facility statedetermining section 3 b is gathered and processed by the facilitymonitoring section 5 to be outputted to the advanced analysis anddiagnosis section 6 on the facility diagnosis center side C via thecommunication network 10.

FIG. 14 shows an example of output of program processing results on theuser side B in the case where the secondary process (advanced analysis)is performed by the facility management data analysis program of the FFTuploaded to the user side B in the facility management data processingsection 3 a as to the measurement point of the channel number “13” inFIG. 8. Moreover, as for the analysis results shown in FIG. 14, the samecontents are sent to the facility diagnosis center side C via thecommunication network 10, and further undergo the advanced analysis inthe advanced analysis and diagnosis section 6 on the facility diagnosiscenter side C.

And the advanced analysis and diagnosis section 6 having received theinformation outputted from the facility monitoring section 5 furtherperforms the advanced analysis and identifies the cause of theabnormality of the facility apparatus 1 concerned and improvementmeasures thereof to send the identified results to the facilitymonitoring section 5 via the communication network 10, and furtheruploads the facility management data analysis program as required to thefacility monitoring section 5 again, which steps are repeatedlyperformed.

In addition, the facility monitoring section 5 gathers and processes atleast one of maintenance information, operation information and externalinformation from at least one of a maintenance information database 13to be a maintenance information section, an operation informationdatabase 14 to be an operation information section and an unshownexternal information database to be an external information section ofthe facility apparatuses 1 shown in FIG. 2 so as to output it to theadvanced analysis and diagnosis section 6 on the facility diagnosiscenter side C.

To be more specific, in addition to the signal processing, the contentsof the secondary process include the maintenance information database 13having the information such as the maintenance planning, facilityspecifications and maintenance history in the user side B storedtherein, the operation information database 14 having the informationsuch as process information, production planning and quality informationstored therein, and the process of gathering the external informationsuch as design specifications and product information of manufacturersand outputting it to the advanced analysis and diagnosis section 6 onthe facility diagnosis center side C.

INDUSTRIAL APPLICABILITY

1. As the present invention has the above-mentioned configuration andaction, a person in charge of the work in the plant on the user sidegrasps and manages operating situation of the facility apparatuses togather various kinds of data on a routine basis, and if the informationfalling under a level of abnormality is extracted from the gatheredinformation, the information is promptly sent to the facility diagnosiscenter side which is the specialized technological group via thecommunication network 10 such as a network, the Internet or a publiccircuit, and on the facility diagnosis center side, the advancedanalysis and diagnosis section can perform the advanced analysis of theinformation and promptly send back to the user side the best informationon the facility apparatus determined to be abnormal, so that the userside can promptly take the measures instructed by the specializedtechnological group based on it.

In addition, the management of facility apparatuses performed based onpersonal knowledge and judgment of the person in charge of the work inthe past is entrusted to the facility diagnosis center side constitutedby technically trained personnel having the expertise so that it is nolonger necessary to station the technically trained personnel at eachindividual plant on the user side, and it is thus possible to improvesafety and productivity of the facility apparatuses on the user side andalso realize improvement in accuracy of the facility apparatusmanagement, increased efficiency of personnel, and reduced total costsof the plants in addition.

In addition, in the case where the advanced analysis and diagnosissection determines that diagnostic accuracy will be improved byperforming the advanced analysis again, it further uploads the facilitymanagement data analysis program, as the secondary process, from theadvanced analysis and diagnosis section on the facility diagnosis centerside to the facility monitoring section on the user side via thecommunication network so that the advanced analysis is performed againon the user side.

The facility management data analysis program is uploaded to the userside and the advanced analysis is performed on the user side again, andthus it is no longer necessary to send to the facility diagnosis centerside the raw data of an enormous information amount such as the facilitystate detecting information detected by the facility state detectingmeans and only a small information amount solely of the analysis resultsis sent to the facility diagnosis center side so that the burden ofinformation transfer on the communication network is alleviated.

In addition, security of the information is improved because the rawdata is not exchanged on the communication network.

1-16. (canceled)
 17. A facility apparatus diagnostic apparatuscharacterized by performing an advanced analysis of information on afacility apparatus outputted from an external apparatus for gatheringand processing the information on a state of a facility apparatus, andidentifying a cause of an abnormality of the facility apparatus andimprovement measures thereof to send the identified results to saidexternal apparatus.
 18. The facility apparatus diagnostic apparatusaccording to claim 17, characterized by being constituted to be capableof mutual communication with said external apparatus via a communicationnetwork and uploading a facility management data analysis program tosaid external apparatus.
 19. The facility apparatus diagnostic apparatusaccording to claim 18, characterized by diagnosing a facility apparatusbased on the information outputted from said external apparatus,extracting a predetermined facility management data analysis programfrom a facility management data analysis program group provided insideand rendering it as an electronic file so as to upload the electronicfile to said external apparatus via said communication network.
 20. Thefacility apparatus diagnostic apparatus according to claim 18,characterized by repeating the steps in which the facility managementdata analysis program is uploaded to said external apparatus, saidexternal apparatus performs a predetermined process by using theuploaded facility management data analysis program and produces output,an advanced analysis of the information outputted from the externalapparatus is performed and a cause of an abnormality of the facilityapparatus concerned and improvement measures thereof are identified tosend the identified results to said external apparatus and also uploadthe facility management data analysis program to the external apparatus.21. The facility apparatus diagnostic apparatus according to any one ofclaims 17 to 20, characterized by being connected to said facilitymonitoring section by a network, the Internet or a public circuit.